Real-time volume rendering of three-dimensional images on a two-dimensional monitor requires a high computing power so that it can only be achieved on supercomputers, high-end workstations, workstation networks or special-purpose hardware. Such rendering would include processing data to view a three-dimensional image from a first angle and then viewing that same image from a second angle to provide stereoscopic viewing. Such rendering would also include viewing different material characteristics sequentially. The high computing requirements stem from the algorithmic complexity of volume visualization and the sheer amount of data to be processed. The visualization of volume data sets typically involves the segmentation, or classification of structures of interest, and their meaningful display on the screen. For example, in a raycasting pipeline, this process can easily turn into 100 operations per raypoint, giving 16GOPS for 256.sup.3 data sets to be rendered at 10 Hz assuming one raypoint per data element on average. Depending on the chosen algorithm and the machine architecture, the needed memory bandwidth can also reach the GByte/s-range.
However, most potential users lack a supercomputer or a high-end workstation. Workstation networks seldom deliver the expected speed due to a limited interconnection bandwidth or heavy loads by other users. Current academic and commercial designs tend to be large, massively parallel architectures (see for example references IX, XII, XIV) and, thus, tend to be very expensive as well.
Although highly desirable in general, interactive classification is not needed in a large number of applications, e.g., when the materials of the data set are well-known, or when automatic segmentation is not reliable enough, and must therefore be done manually by human specialists (for example, in medical diagnosis).
Classification can be considered a preprocessing step, performed once before a large number of views are produced. For a comprehensive understanding of the data set, however, a number of requirements should be satisfied. First, preferably the users should be placed into a virtual environment, where they can step right through the data set to gain the maximum insight. Second, the system must preserve the three-dimensional nature of the data, provide perspective views and retain the depth information. Next, if the data set can be classified into different materials, it should be possible to display either one of them or any combination translucently without performing a re-classification. Finally, the system must provide high rendering speed and high image quality. However, for a broad acceptance on the market, a volume rendering accelerator should not increase the price of a graphics workstation or even a PC significantly.
It is therefore an object of this invention to make the benefits of volume rendering available to a wide audience (e.g., in medical education) and to reduce the costs of a volume visualization system.